Innovations in methodology
The department is a leading centre of expertise in social research methodology with particular strengths in survey research methodology, secondary analysis of cross-sectional, multilevel and longitudinal datasets, qualitative methodology, social simulation, statistical modelling, methodological integration, virtual methods, and new technologies for social research. There is a special interest in the use of mixed methods, methodological triangulation, and the methodological integration and issues of cross-national comparative research.
This work is integrated through its specialist advanced methodology centres, including CRESS, the Centre for Research on Simulation in the Social Sciences, directed by Prof. Nigel Gilbert and CAQDAS, the Computer-Assisted Qualitative Data Analysis Networking Project, directed by Prof. Nigel Fielding.
Thus, members of the group are closely involved in methodological research in fields such as the development of social simulation methodology, the improvement of social measurement in social survey research and the dissemination of good practice, and analysis of the use made by researchers of qualitative data analysis software.
Individual members of the group are also engaged in the development and refinement of techniques of secondary analysis (both quantitative and qualitative), in using new online and web-based research methods, and in triangulation and exploring the complexities of multi-method methodologies in sociology.
Funding for our work has come from a variety of bodies, notably the Methods and Infrastructure Committee of the Economic and Social Research Council, but also from other diverse sources such as the German Central Data Archive, NATO, Research Talk Inc., Sage Publications Ltd and associated companies.
The QUIC (Qualitative Innovations in CAQDAS) a former Node of the National Research Methods Centre (NCRM), was an ESRC funded project concerned with the integration and analysis of multiple data sources using CAQDAS software and the dissemination of such techniques through a training and capacity building programme. Qualitative software support will be explored for integrating qualitative and quantitative data in mixed methods research, for the analysis of Access Grid multi-stream visual data and for the integration of geo-referenced data within qualitative analysis. Outputs from this project can be found on the CAQDAS Networking Project website.
The SIMIAN (Simulation: a Node) project, another former NCRM Node, was funded by the ESRC to promote and develop social simulation in the UK. It involved three "demonstrator" simulations chosen to address important social science challenges: Repeated Interaction, Novelty and Norms. These three demonstrators formed the basis for a range of training and capacity building activities across the UK.
An NCRM collaborative fund project titled Innovations in Social Science Research Methods: An International Perspective, was funded by the ESRC to identify innovative methods in the social sciences outside the UK; a follow up workshop was organised adjacent to the NCRM Festival in 2010.
Christine Hine has recently been involved in organising a Network for Methodological Innovation funded by the National Centre for Research Methods, focusing on Digital Methods as Mainstream Methodology
An ESRC funded study investigating the methodological issues that arise in multi-method and multi-level approaches to a research question concerned with how ‘vulnerability’ is perceived, experienced, and responded to, in everyday life and at the planning/policy level (PPIMs);
An assessment of the implications for qualitative research practice of E-Social Science, including grid-based applications for work with streaming video, the role of Access Grid Nodes in research collaboration and HPC-based content analysis.
Start date: 1 January 1994
End date: 13 December 2011
The project received seven consecutive terms of funding by the UK Economic and Social Research Council, with no commercial links to any software developer or supplier. It aimed to provide practical support, training and information in the use of a range of software programs designed to assist qualitative data analysis. The project also provided various platforms for debate concerning the methodological and epistemological issues arising from the use of such software packages. The CAQDAS Networking Project also encompassed an additional project, Qualitative Innovations in CAQDAS (QUIC), funded by the National Centre for Research Methods (NCRM) which explored three new breaking developments in the use of CAQDAS alongside the training and capacity building activities.
ESRC Researcher Development Initiative
Start date: 1 January 2012
End date: 31 December 2013
This project aims to increase students’ knowledge and use of QM amongst HE1 Sociology students. The project will do this via i) increasing Level 1 sociology teaching staff’s familiarity with QM to support ii) integrating substantive and QM teaching across the Level 1 programme. The project emphasises the ‘full integration’ of QM skills into the undergraduate curriculum in a manner that ensures quantitative literacy is achieved early, occurs frequently and is integrated with approaches that account for students’ different learning styles.
The practical goals of the project are:
(1) Full integration: As relevant and in ways that respect the learning outcomes of the individual modules, the same materials/exemplars are used across substantive and quantitative modules so that students get repeated exposure to the same information in different contexts.
(2) Full coverage: To integrate QM and substantive teaching across the whole of the Level 1 curricula.
(3) Full support: To ensure full support from all Level 1 module convenors and tutors and the departmental management group.
(4) Full provision: To develop online resources that supplement other modes of teaching and support all Level 1 modules.
- Dr KA Bullock
- Dr IR Brunton-Smith
- Dr RAL Meadows
- Prof LP Cooke
- Dr SM Earthy.
Start date: 1 September 2010
End date: 31 August 2013
MILES (Models and Mathematics in Life and Social Sciences) is a new three-year programme of events and funding opportunities to stimulate interdisciplinary research collaborations across the University of Surrey. MILES will stimulate and foster projects that bring together academics from mathematics, computing, physical sciences and engineering with those from the life and social sciences and beyond. MILES events will include networking and idea-generation activities, opportunities to showcase and discuss existing interdisciplinary research and workshops designed to support the development of collaborations.
- Rebecca Hoyle
- Nigel Gilbert
- Paul Krause
- Johnjoe McFadden.
Start date: 15 November 2010
End date: 31 October 2011
Multilevel models (MLM) have pioneered the analysis of data that have a hierarchical structure with two or more 'levels'. They have been developed within a statistical paradigm, primarily as a method of describing and analysing large data-sets. Agent-based models (ABM) are also used to analyse social phenomena in which are there are two or more 'levels' involved, often called the micro- and macro- levels. ABM were developed from a non-statistical background, drawing on artificial intelligence and physics. Agent-based modelling usually follow a deductive or abductive methodology, testing a model against data, while multi-level modelling is often inductive, deriving a model from data. MLM allow the user to make inferences with known confidence, which is generally not true of ABM, while ABM are capable of modelling non-linear, complex systems with emergent behaviour. Thus to some extent the two modelling 'paradigms' are interested in the same kind of issues but approach them from entirely different directions and have different strengths. The aim of this short study is to clarify the similarities and differences between the two styles of modelling, attending to the modelling of levels, and to investigate whether there is value in the integrating some aspects.
ESRC through National Centre for Research Methods (NCRM)
Start date: 1 September 2008
End date: 1 September 2011
The QUIC Research Node is a Node of the ESRC National Centre for Research Methods. The Node will continue to deliver its highly-regarded Training and Capacity Building programme in qualitative software, but will also explore three new breaking developments. The first concerns the support that CAQDAS offers to bring together qualitative and quantitative data in mixed method research designs. The second relates to multi-stream visual data. Social science increasingly uses visual data, and a new technology called the 'Access Grid' allows people at many locations to participate in 'virtual fieldwork' or teaching sessions convened by a host site. The Node will document how to analyse AG multi-stream visual data using CAQDAS, and deliver training via AG. The third development concerns a technology many drivers have encountered, the GPS navigating system. We designed a tool to do crime and disorder audits in neighbourhoods and now plan to add GPS to it, enriching its qualitative output. Also, developers are now providing Google Earth utilities in CAQDAS software. Putting these things together will enable users to add a spatial dimension to their analyses of qualitative data. The Node will explore the three new areas in relation to one broad topic: environmental risk. Two will be tested in mini-research projects concerning social factors in response to natural environmental risk arising from climate change, and the third in social environmental risk arising from crime/disorder. We will derive exemplars, teaching data sets, and self-learning materials from each mini-research project and transfer these to our Training and Capacity Building programme.
ESRC National Centre for Research Methods
- Nigel Fielding- Node Director
- Jane Fielding - Node Co-Director
- Ray Lee (Royal Holloway, University of London) –Node Co-Director
- Ann Lewins - TCB Research Fellow
- Christina Silver - TCB Research Fellow
- Thomas Koenig - MICS Research Fellow
- Graham Hughes - MICS Research Fellow
- Zoe Tenger - Administrator